This paper conducts a comprehensive study on predicting the cross section of Chinese stock market returns with a large panel of 75 individual firm characteristics. We use not only the traditional Fama-MacBeth regression, but also “big-data” econometric methods: principal component analysis...

Many anomalies are based on firm characteristics and are rebalanced yearly, ignoring any information during the year. In this paper, we provide dynamic trading strategies to rebalance the anomaly portfolios monthly. For eight major anomalies, we find that these dynamic trading strategies...

We propose a novel measure of the ex-ante commodity downside-risk premium (CDP) for each commodity based on a term structure model of commodity futures. Our theory-based CDP, capturing forward-looking information in the futures markets, outperforms well-known characteristics in explaining the...

What predicts returns on assets with "hard-to-value" fundamentals, such as Bitcoin and stocks in new industries? We propose an equilibrium model that shows how rational learning enables return predictability through technical analysis. We document that ratios of prices to their moving averages...

We provide an entropy approach for measuring asymmetric comovement between the return on a single asset and the market return. This approach yields a model-free test for stock return asymmetry, generalizing the correlation-based test proposed by Hong, Tu, and Zhou (2007). Based on this test, we...